Up-skilling your workforce’s data capacities is crucial to stay competitive. But learning data is hard: what is going to motivate individuals to keep at it?
A cardinal rule of education is to “design with the learner in mind,” so before building the data academy, it’s important to understand learner motivations.
A 2015 study by the learning consultancy Towards Maturity (now EmeraldWorks) found the following motivations for online professional learning:
- 75% want to be able to do their job faster and better
- 51% like to learn just for personal development
- 50% want to be eligble for promotion
- 47% want to obtain professional certification
- 41% want to be enabled to earn more money
- 39% want to keep up with new technology
- 35% want to achieve/maintain a higher certification level
- 35% want to increase productivity
- 22% want to pass an assessment
- 10% want to compete against colleagues for a high score.
You can check out the complete study here.
These points got me thinking about implications for designing a data academy. The more the academy’s designed around the motivations of the learner, the more it will succeed.
People learn data to cut back on copy-pasting
76% want to do their job faster and better
A survey from the technical publisher Packt found that data cleaning is the least favorite part of the data analysis process among 50% of data professionals… which is unfortunate, because data professionals spend the majority of their time doing it.
I got into data analytics for this very reason: I was tired of slow, error-prone analysis and reporting. I wanted to automate the boring stuff.
A solid data training program will bring this motivation to the fore, helping students automate their workflow. This is better for everyone: your learners will feel more fulfilled and less stressed about their work, and the organization benefits from increased morale and more reliable data.
People learn data to have fun
51% learn for their own personal development
It’s easy to discount this one… but learning should be fun! Even die-hard professional learners often do so for pure curiosity and enjoyment.
Your data training program doesn’t need to be all business — it can and probably should include examples from sports, movies, baby names, you name it. People already enjoy crunching this kind of data, as endless online listicles make clear.
With the right training, leaners will see data analysis as a mode of inquiry, and even a means of creativity. A solid data education helps people see the art and innovation in what they are doing with spreadsheets, which is one of the best ways to plant data literacy into an organization.
Reward those who learn data
50% want to be eligble for promotion
47% want to obtain professional certification
41% want to be enabled to earn more money
While your learners will revel in their new productivity, and the office football pool may get “Moneyballed,” don’t forget to reward in tangible ways, too.
Learning data is hard work, but without data talent your organization will fail. You may try to hire a couple of data scientists to make the problem go away, but for reasons I’ve written about before, that solution won’t work.
The best managers reward credit where it’s due, and data training programs should chart a path to raises, promotions, and sponsored certifications. In the scheme of things, it’s the most logical and efficient way to building a data culture over endless turnover and expensive systems to nowhere.
Designing with the data learner in mind
Building a data academy takes a lot of work, but so does enrolling in it. Don’t overlook your students’ motivations, but weave them into the core of the academy for a more successful and sustainable outcome.
To talk more about building a data academy, feel free to drop me a line, or book a free call.
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